Activity monitoring has become popular in the fitness arena. People want to count the number of steps, decipher time spent or calories burnt on activities (e.g., walking, running, jumping, cycling), monitor their heart rates, and so forth. As several examples, mobile activity monitors may include various sensors, such as accelerometers, gyrometers, magnetometers (compasses), pressure sensor, GPS (global positioning system) receiver, and the like. However, the sensors, sensor blocks, and associated components included in activity monitors may consume substantial amounts of power, which can drain the batteries of mobile devices. For instance, the sensors may continually run at full speed, collecting large amounts of data. A sensor block may receive the data, and may often transmit the data wirelessly to another device. Further, in some examples, the sensor block may encrypt this data. Accordingly, conventional sensor blocks that receive and convey sensor signals may consume a substantial amount of power.
As an example, suppose an activity tracking device includes a sensor generating a signal in which the signal bandwidth includes frequencies up to 1 KHz. Thus, an analog-to-digital converter (ADC) may need to perform sampling of the analog signal at a rate of at least 2 KHz, which is the Nyquist rate of the highest frequency in the signal. In addition, a transmitter may need to transmit at that same rate, i.e., 2 KHz. Thus, when present, a transmitter may consume a large percentage of the total power consumed by the device. Further, other components of the device may also need to run at or above the Nyquist rate to match the operating speeds of the ADC and the transmitter.
In addition, a computing device that receives the data from the activity tracking device may need to store the large amount of sensor data and may further process the data. For example, the computing device may perform a substantial amount of data analysis and may generate a visual display of the data obtained by the sensor and sensor block of the device. Receiving and processing these large amounts of data may lead to high storage costs and may consume a significant amount of processing time and power.
Furthermore, ensuring security of the sensor data sent from the sensor block to the computing device may also drain considerable resources. For instance, sending data over wireless links may employ some mode of encryption, which may consume additional power and resources of the sensor block.